2024/05/23 by Bianka Bakullari, Bakullari, Bianka, Wil M. P. van der Aalst +1
Business, Management and Accounting · Computer Science · Decision Sciences · #Big Data and Business Intelligence #Data Mining Algorithms and Applications #Data Quality and Management #Databases (cs.DB) #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.2405.14435
openalex publication_date 2024/05/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Process mining traditionally relies on input consisting of low-level events that capture individual activities, such as filling out a form or processing a product. However, many of the complex problems inherent in processes, such as bottlenecks and compliance issues, extend beyond the scope of individual events and process instances. Consider congestion, for instance, it can involve and impact numerous cases, much like how a traffic jam affects many cars simultaneously. High-level event mining seeks to address such phenomena using the regular event data available. This report offers an extensive and comprehensive overview at existing work and challenges encountered when lifting the perspective from individual events and cases to system-level events.